In the contemporary world of research, the possibilities for data analysis are expanding exponentially through the use of both new and old tools. Many resources exist at the University, in the Bay Area, and across the internet for acquiring skills valued in both academic and professional fields—you just have to learn how to access them. Steps You Can Take Attend On-Campus Lectures, Training Sessions, and Working Groups The Berkeley D-Lab offers many resources for acquiring computational and technical skills. In particular, the tools, methods, and techniques that D-Lab teaches scholars in the social sciences and digital humanities provide the ability to engage with complex research questions and produce answers that benefit academic colleagues, policymakers, and the public. D-Lab training workshops focus on a wide range of topics—from Text Analysis Fundamentals and Preparing Your Data for Qualitative Data Analysis to Introduction to Georeferencing and Introduction to Artificial Neural Networks—and a variety of platforms and programming languages, such as Excel, R, Python, and more. The D-Lab also hosts working groups such as the Computational Text Analysis Working Group, the Machine Learning Working Group, and the Berkeley Digital Humanities Working Group. Explore the D-Lab events calendar to see how your research might benefit from new possibilities in computational technology. The D-Lab also hosts a team of consultants who offer free daily appointments and drop-in hours for advising and troubleshooting on qualitative and quantitative research design, modeling, data collection, data management, analysis, presentation, and related techniques and technologies. Use Academic Breaks to Attend Intensive Skill-Building Programs Many campus programs and centers offer high-intensity short-courses that take place during the spring or summer breaks. For instance, the Berkeley Extension offers a Summer Coding Boot Camp, while Digital Humanities at Berkeley hosts their own Summer Institute that is free and open to all faculty, staff, postdocs, and graduate students affiliated with Berkeley. Across campus, the Geospatial Innovation Facility (GIF) offers the spring break Spatial Data Science Bootcamp, a 3-day certificate program designed to familiarize participants with major tools and advances in geospatial technology, including big data wrangling, open-source tools, and web-based mapping and visualization. These types of programs typically offer certificates of attendance or completion that should be listed (when relevant) on a CV or resume—in addition to the competencies they explicitly provide, they also attest to your ability to acquire a host of new skills in a short period of time. Get Funding and Other Forms of Support to Develop the Skills You Need Obtaining research funding bears evident value in enabling your research to thrive, but also helps boost your resume by demonstrating that you have a successful grant application history—a boon in any academic or non-academic career. At Berkeley, many types of support exist to facilitate your research. For instance, the university library’s Data Acquisitions and Access Program leverages research funds to provide access to data (numeric or textual) that requires purchase or licensing, or is otherwise restricted. More traditional grant- and fellowship-based forms of funding are also available. In addition to the Graduate Division’s list of external fellowships and fellowship opportunities included in the GRAPES database, both the Berkeley Research Development Office and the Berkeley Sponsored Projects Office maintain lists of funding opportunities. The Research Development Office offers consultations to discuss and develop funding strategies according to the research needs of a particular project. In addition, university centers such as the Geospatial Innovation Facility or the Digital Humanities at Berkeley typically offer more targeted information about funding sources for students working in those fields. Berkeley also offers a variety of mentoring programs, including one—the SMART program—which is directly designed to facilitate graduate research by offering funding and undergraduate research assistance on a proposed project. Explore Bay Area Skill-Building Resources As the home to Silicon Valley and multiple world-class universities, the Bay Area is an ideal location for those interested in learning, using, and building careers around computational and technical skills. Thanks to the Intercampus Exchange and Stanford-Berkeley Exchange programs, graduate students with a superior academic record may take a limited number of courses that are offered at Stanford or one of the other UC schools, and have the opportunity to make use of special facilities and collections and associate with scholars or fields of study not available on their home campus. Students looking to build computational or technical skills may also wish to participate in workshops or attend events at area hubs like the Stanford Literary Lab. Groups also exist for connecting locals with technical skills to burgeoning employment opportunities. For instance, Bay Area Codes is an online resource to connect Bay Area residents to local tech opportunities, while Tech SF (a branch of the Bay Area Video Coalition) seeks to help unemployed tech professionals get the skills they need for a continually changing job market. Take Advantage of Online Skill-Building Resources Many discipline-specific, interdisciplinary, and generalist resources exist online for those seeking to expand their technical repertoire—particularly in the realm of computational skills. For instance, the DiRT (Digital Research Tools) Directory provides a guide for finding and comparing resources ranging from content management systems to OCR (optical character recognition), statistical analysis packages to mindmapping software. Similarly, the Institute for Digital Research and Education offers resources, events, and consulting for UC-affiliates, including a wealth of materials accessible online. BerkeleyX provides free online courses in a variety of subjects for currently enrolled students, while sites like Coursera, Code Academy, and Code School offer a mix of free and low-cost training sessions.